Marketing to Focus on Customer. Analytics?

It’s been very popular among marketing types to talk about “the customer” but seek metrics for affirmation other than those based on or derived from the customer. Web analysts have followed their lead, and provided Marketers plenty of awareness, engagement, and campaign metrics. As I’ve said inthe past, this is a huge disconnect. Does it make sense (analytically) to have discussions about customer centricity, customer experience, customer service, the social customer, etc. and measure these effects at the impression or visit level?

Is someone who visits or purchases or comments one time really a customer, for the purposes of analyzing “centricity” ideas and concepts? I think not. Visit metrics simply don’t work for understanding these customer concepts, because by definition they unfold over time, not as single events. Add in the fact most web activity is 1x in nature – even buyers – and you begin to realize that analyzing “traffic” yields very little in the way of “customer” insight.

From a Marketing perspective, hey, happy to have the 1x revenue, but these are interactions I’m not really excited about increasing spend on, knowing they will be a one-night stands. This is especially true when you also know re-allocating some of the funds spent on the 90% 1x-ers to the other 10% could double company profits!

If you have followed my writings over the past 12 years, none of the above perspective is new. What might be changing is this: more people in the online world are beginning to think the same way.

Now comes eConsultancy with a review of “major trends in marketing and technology” that lead to some key takeaways, which they outline here. Marketers, they say, are moving towards customer-based metrics, and the organization has to be prepared for change.

I’ve been through this change several times before. My experience is this: as an organization moves from campaign or funnel-based metrics to metrics based on customer value over time, old beliefs are shattered and new ones need to be accepted.

Take, for example, the eConsultancy comment on attribution:

“Organizations have to be prepared for the changes that attribution should cause to media mix and budget. If compensation packages are still tied to siloed spending, there will be resistance to adopting an attribution-based model.”

Wow, resistance? Maybe full out internal warfare, if you ask me. When people have paychecks tied to metrics, things can get ugly in a hurry if these same metrics turn out not to be in the best interest of the company (metrics are not authentic KPI’s).

Implications of this change

What could this change mean for web analysts? In fact, much of your approach to the work, the thought process, the general concepts, do not change. But as you might imagine, changing how success is defined from a visit-based value model to a customer-based value model can radically impact perception of “what works”.

Beneath what eConsultancy is saying, the driving principle for the tension, is that customer value metrics are the universal yardstick of success, because they can be used across any platform, media, and channel, allowing direct comparison of performance across programs in any silo. Think about what that means.

Customer metrics are the end of silos hiding behind metrics customized to prove their own success and grab budget. If the silo can’t move the needle at the customer metrics level, well, it doesn’t really matter what the metric championed by the silo says. That silo-based, tortured to make us look good metric is now obsolete.

As you might guess, this kind of thing creates considerable organizational tension. When there is a move from “campaign” analytics to customer analytics, winning ideas can become losers, and quite often, losers become winners.

Take conversion, for example. Did you know it’s common for campaigns with both high volume and high conversion rates to create the lowest value customers? Are web analysts and surrounding silos ready for that, to accept the campaigns they are most proud of are in fact the poorest performing when the “value” goal posts are moved?

As the marketers move towards managing by customer metrics, conflicts like this will definitely surface. Does management want short-term conversion / sales or long-term customer value / profit? Who decides? How will people be compensated?

This won’t happen overnight or next year or perhaps in 5 years time for many companies. Leading companies with a proper analytical culture in place, especially those that face extreme competition, are already managing by customer value, because they must to survive. Lots of others will follow slowly. This will be especially true if Gartner is correct in the analysis mentioned here:

“In fact, industry watchers say today’s CMO must become the de-facto chief customer officer — or lose out. CMOs have historically been the brand steward. This is an opportunity to be a customer steward”. Love the subtitle on that article: And If They Don’t, They’ll Be Relegated to Overseeing Promotions While Someone Else Takes Chief Customer Officer Role.

I’d guess “Relegated” is not a scenario most CMO’s are interested in…but is a correct assessment. Why?

The nature of customer analysis is that it often ties very closely to company finances and quarterly reporting, meaning natural alignment with strategic issues and on up to the C-Level folks. A universal success metric like customer value that is valid and actionable across any program or platform creates the ability for the org to manage all aspects of the business using analytics, because apples can be apples no matter where they are grown – Marketing, Customer Service, Merchandising, etc. Also true: it’s much easier to determine the source of bad apples, no matter which silo is generating them.

This enables the C-Level to finally start managing using analytics, rather than just nodding and saying the reports are interesting. Since customer analysis often allows C-Level folks to act on problems before they become income and profit issues, customer analysis ideas and metrics are often quickly embraced once proven to be valid.

This is what many web analysts have wanted, right? Respect and buy-in for analytics from the C-Level?

On a practical level, using the same yardstick to measure success across any silo means budgets can be reallocated not just within a silo, but across silos. For example, seeking the highest value, Marketing budget could be reallocated to Customer Service, if certain programs in Service are found to generate much higher customer value than some in Marketing.

What’s a (web) analyst to do?

The first question for web analysts is how they will handle the transition. Here’s what you do not want to happen. You are sitting in a conference with high level execs talking about how great a certain campaign is performing, and the customer analyst says, “Actually, that campaign the web analytics folks are telling you is a success is one of the worst performing campaigns we have, in terms of customer value created”.

Ouch. This happened to me early in my marketing career, when I concentrated on the results of campaigns as opposed to impact on customer value. I know what it feels like, and it’s not fun.

So, if you’re not doing the customer analysis yourself, make sure you are in the loop with those folks. Help them figure out how to properly integrate web data into the customer analysis stream, and get yourself an inside look at how it all works. Don’t make this transition a battle between the web analysts and the customer analysts.

Ouch. This happened to me early in my Marketing career, when I concentrated on the results of campaigns as opposed to impact on customer value, which translates to profits and stock prices. I know what it feels like, and it’s not fun.

So, if you’re not doing the customer analysis yourself, make sure you are in the loop with those folks. Help them figure out how to properly integrate web data into the customer analysis stream, and get yourself an inside look at how it all works. Don’t make this transition a battle between the web analysts and the customer analysts.

The second question is this: as marketers move towards customer analysis, who will be doing this customer analysis? Are current web analysts interested in doing it? Or will someone else – maybe in Finance, maybe a BI unit, maybe an outside agency – be providing this service to the org?

I’ll go out on a limb here and say most web analysts with more than 5 years experience are not only capable of doing customer analysis, they’d be really good at it. Segments, experience paths, value creation – you got a handle on that? Same general idea.

The biggest difference is simply the time frame of the analysis – analysis is not over when the initial goal is achieved; the org wants to know what value is created downstream by the customer – 3 months later, 6 months later, a year later. Does the customer come back and take action again? What is the downstream value created by this campaign versus that campaign, this content versus that content, this product versus that product?

Same general ideas a web analyst works with all the time, with a longer “tail” on the measurement of success or failure.

Sure, at the tool level there can be a difference between web analytics and customer analysis , depending on which WA tool you are using – more advanced tools often have native capabilities for customer analysis. But the hardest part, the analytical mindset, most web analysts have got that covered. And on the tools, if your WA tool lacks the chops, we’re talking about simple customer database queries and spreadsheets to start – is that so hard?

I doubt it, for the WA folks I know. If the analyst doesn’t have database query skills (as I do not, ’cause I’m a Marketing guy), they know people who do, either within the company or as contractors. Customer analysis is not nearly as difficult as many people would like you to think it is, there is a middle ground between doing nothing on customer analysis and working with regression models, neural networks, and other “Big Data” promised lands.

Then, once you define the impact of using customer value as a universal yardstick for success across the silos, you have made the investment case for moving up to specialized tools that allow automation and discovery, then on to modeling and prediction.

So, I’m just checking – isn’t this a path web analysts have been asking for? C-Level attention and follow-through, an org that respects analytical work and will “do something” based on the analysis?

Are you up for measuring, understanding, and driving business action using models and concepts that can make an even greater impact on the business than what you do now with web analytics?